TL;DR: Users never give complete instructions — they give partial signals and expect the system to fill in the rest. Most AI memory solutions try to “remember more.” The fix is filling in the half ...
Chat-based document editing feels exhausting because it fights how your brain works. You lose spatial memory, overload working memory, and constantly switch between evaluating and instructing. The ...
TL;DR: A playbook captures how to do things. It cannot capture whether to do them (strategic intuition) or how to make them actually happen through people (lubrication). If your job can be distille...
TL;DR: Two ideas from Anthropic’s growth team that broke my priors: adding friction to onboarding increases conversion when your product has a discoverability problem, and AI-first companies should...
TL;DR: Twelve months ago, AI agents looked like a new species that invalidated everything we knew. Then Anthropic decomposed agents into Brain, Hands, and Session — and out fell event sourcing, sta...
TL;DR: When a small model claims 128K context, it means the positional encoding goes that far. It doesn’t mean the model can actually use it. Most on-device models have an effective context of 8-16...
TL;DR: Last month I wrote about three paths to local AI (BitNet, quantization, engine optimization). Gemma 4 just added a fourth: architecture efficiency. Here’s how all four fit together — and wha...
TL;DR: AI agent security maps 1:1 to patterns we solved decades ago — firewalls, IDS, DPI, defense in depth. The defense playbook is ready. The real bottleneck? Agent Identity. Until agents have st...
TL;DR: Eric Schmidt says universities should teach AI tools from day one. He’s confusing education with training. Universities exist to build judgment, not tool proficiency. That distinction matter...
TL;DR: Musk frames Optimus as an answer to US-China competition. But the real question isn’t which country builds more robots — it’s who captures the value when robots replace workers. He dressed u...